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Baixe weiss2010d e outras Notas de estudo em PDF para Arquitetura, somente na Docsity! ITS 2010: Displays November 7-10, 2010, Saarbrücken, Germany 1 BendDesk: Dragging Across the Curve Malte Weiss Simon Voelker Christine Sutter Jan Borchers RWTH Aachen University 52056 Aachen, Germany {weiss, voelker, borchers}@cs.rwth-aachen.de christine.sutter@psych.rwth-aachen.de ABSTRACT We present BendDesk, a hybrid interactive desk system that combines a horizontal and a vertical interactive surface via a curve. The system provides seamless touch input across its entire area. We explain scalable algorithms that provide graphical output and multi-touch input on a curved surface. In three tasks we investigate the performance of dragging gestures across the curve, as well as the virtual aiming at targets. Our main findings are: 1) Dragging across a curve is significantly slower than on flat surfaces. 2) The smaller the entrance angle when dragging across the curve, the longer the average trajectory and the higher the variance of trajecto- ries across users. 3) The curved shape of the system impairs virtual aiming at targets. ACM Classification: H5.2 [Information interfaces and pre- sentation]: User Interfaces. - Input Devices and Strategies. General terms: Design, Human Factors Keywords: Curved surface, desk environment, multi-touch, dragging, virtual aiming. INTRODUCTION A typical computer workplace integrates horizontal and ver- tical surfaces into a workspace. It encompasses at least one or more vertical displays that show digital content and a larger horizontal area, containing input devices, such as mouse and keyboard, paper-based documents, and everyday objects. Touch recognition technologies have combined the benefits of traditional input metaphors with digital documents [24]. Tablets allow high precision stylus input for graphic design; digital pens, such as Anoto1, enable annotations on physical paper; and multi-touch gestures [4] provide an intuitive way to transform and modify digital data. However, despite all the advantages these interfaces have barely found their way into everyday workspaces yet. 1www.anoto.com Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. ITS’10, November 7-10, 2010, Saarbrücken, Germany. Copyright 2010 ACM 978-1-4503-0399-6/10/11...$10.00. Figure 1: BendDesk seamlessly merges a horizontal and a vertical interactive surface with a curve. Many systems have been proposed that use vertical and hor- izontal interactive surfaces within a single desk environment (e.g., [7, 16]). They provide a large interactive area and allow to move digital objects across multiple displays. However, those systems suffer from a lack of spatial continuity. Ac- cording to the Gestalt Law of Closure [5], gaps between ad- jacent displays suggest isolated interactive areas. Other laws may be violated that are useful in screen design, e.g., the Law of Proximity, because objects belonging together may be sep- arated across the gap. Furthermore, splitting objects across bezels impairs search accuracy and tunnel steering perfor- mance [2]. Finally, those setups limit the applicability of di- rect manipulation, as movement trajectories are interrupted when dragging a finger or pen from screen to screen. In this paper, we present BendDesk, a desk environment that merges a vertical and a horizontal multi-touch surface into one interactive surface using a curve (Figure 1). Our system provides a large interactive area within the user’s reach and allows uninterrupted, seamless dragging gestures across the entire surface. The focus of this paper is to explore the ef- fects of a curve between two orthogonal surfaces on one of the most basic gestures: dragging. Our results can inform the design of more complex gestures, as most of these can be subdivided into elementary dragging and pointing opera- tions. ITS 2010: Displays November 7-10, 2010, Saarbrücken, Germany 2 (a) Placing of projectors and cameras. board curve tabletop (b) Interactive areas of the BendDesk system. (c) Manual screen calibration. Figure 2: Hardware setup and screen calibration. RELATED WORK Our project was inspired by the Sun “Starfire” video pro- totype from 1994 that intended to predict a potential future workplace in 2004 [23]. The envisioned system featured a large, interactive area, different input modalities such as ges- tures and direct manipulation, and applications, such as re- mote collaboration. In recent years, the specific characteristics of horizontal and vertical interactive surfaces have received great interest in the research community. According to Morris et al. [18], horizontal surfaces are more appropriate for annotation and pen-based note-taking, while vertical displays support read- ing and intensive writing tasks using keyboards. Since no display seems appropriate for all potential tasks, Morris et al. propose a hybrid system. In a later paper [17], they re- port on a field study involving multiple horizontal and ver- tical screens. Although participants were enthusiastic about the extra space, one problem reported was that the horizontal and vertical screens were perceived as isolated areas. Some studies [17, 19] indicate that interactive surfaces should al- low tilting to increase comfort, such as the FLUX table [15]. However, Morris et al. also emphasize that desk environ- ments should fit into the ecologies of objects. For example, a table should allow users to put down everyday objects. This coincides with observations in a long-term study by Wigdor et al. [26]. The authors point out the “dual use” of interactive tabletops as computing devices and as pieces of furniture. In their study, the participant tended to tilt the table at an angle that avoided objects to fall from the table. The combination of horizontal and vertical interactive sur- faces has mostly been applied to two applications: collab- orative workspaces and remote desks. While tabletops are suitable for face-to-face group work and provide awareness of each other’s actions, interactive boards can provide an overview of information shared among groups. Accordingly, many systems have been developed that integrate vertical and horizontal interactive surfaces into collaborative workspaces in order to add digital capabilities [8, 13, 21, 25]. The incor- poration of both surface types has also been applied to remote desk environments. For example, the Agora system [16] and DigiTable [7] provide an interactive horizontal surface for a private document space and a vertical surface displaying a re- mote person via a video conferencing system. However, the vertical surface is non-interactive in most of these systems. Nearly all multi-touch systems are limited to one or more flat interactive devices. One exception is Sphere [1], a spherical multi-touch enabled display. Furthermore, the field of or- ganic interfaces [6, 11] proposes interactive non-planar sur- faces that can be freely deformed. Early examples of this vision are Paper Windows [12] and Gummi [22]. Recently, Curve [28] presented ergonomics and design considerations for building a curved multi-touch table. DESIGN CONSIDERATIONS We envisioned BendDesk as a multi-touch desk environment that supports interaction with digital documents but also re- spects the nature of traditional desks. Although there is ev- idence that tilted surfaces yield high acceptance for specific tasks (see above), we intentionally avoided them for two rea- sons: Firstly, we consider the support of the ecology of (ev- eryday) objects as crucial. With the exception of special pur- pose desks, such as drawing tables, office desks are usually horizontal because people put physical objects on them. In contrast, the possibilities of placing objects onto a tilted sur- face, even at small angles, are limited. Secondly, tilting the vertical surface backwards would reduce its reachability at the top. We also accounted for ergonomic requirements: the user should be able to sit in a comfortable position and to reach the entire input area without much effort. We applied ISO norm 9241-5 to choose the height of the table. Furthermore, we conducted preliminary user tests on an adjustable table prototype to find the depth for the vertical surface. In these tests, users perform pointing and dragging tasks where the depth of the vertical surface was varied. HARDWARE SETUP As illustrated in Figure 2, our interactive desk consists of one 104 cm × 104 cm acrylic surface that is bent to yield two orthogonal surfaces, seamlessly merged by a curve. The sur- face is mounted at 72 cm height2, on a half-closed wooden box that contains all electronics, such as projectors for graph- ical output and cameras for touch input. The form factor of our setup separates the device into three interactive areas: the vertical board (100 cm × 43 cm), the curve (100 cm × 16 cm) with a radius of 10 cm, and the horizontal tabletop (100 cm× 40 cm). We choose a radius of 10 cm to provide a large 2following ISO 9241-5 ITS 2010: Displays November 7-10, 2010, Saarbrücken, Germany 5 (1) horizontal (2) curve x-position(1) (2) (3) (4) (5) (6) (7) (3) vertical upwards downwards area Figure 4: Experimental design of vertical dragging task. cm), the interactive area went blank and the next trial was displayed. They appeared in three different areas (in the hor- izontal plane, the curve, or the vertical plane), and dragging direction from source to target was either upwards or down- wards. This resulted in 3 (area) × 2 (dragging direction) ex- perimental conditions. We further controlled the distribution of trials across the surface by presenting trials on seven dif- ferent x-positions with two repetitions each. The order of tri- als was randomized. Participants worked throughout 84 tri- als with their dominant hand and throughout another 84 trials with their non-dominant hand. This yielded a total number of 168 dragging operations per participant. Dragging duration was defined as the interval from touching the source until correctly releasing it when the source was placed in the tar- get (given in ms). Dragging trajectory covered the observed length of the finger’s movement path, again from touching the source until correctly releasing it when the source was placed in the target (given in px). We hypothesized the following outcomes: • H1 (horizontal vs. vertical): Dragging (a) duration and (b) trajectory are shorter on the horizontal surface than on the vertical one. • H2 (planar vs. curve): Dragging (a) duration and (b) tra- jectory are shorter on planar surfaces than on the curved area. • H3 (down vs. up): Dragging (a) duration and (b) trajectory are shorter when moving upwards in GUI coordinates than when moving downwards. Results The data were analyzed for each of the dependent variables with 3 × 2 analyses of variances (ANOVAs) with the within-subject factors area and direction. Dragging dura- tions are depicted in Figure 5. The ANOVA revealed a signif- icant main effect of the factor area (F (2, 34) = 14.20; p < 0.01). Dragging durations inside the curve (mean 1166 ms) were 14% (150 ms) longer than the dragging durations on ms 800 900 1000 1100 1200 1300 horizontal curve vertical Directions down up Figure 5: Dragging duration depending on area and direction. Whiskers denote 95% confidence interval. px 150 155 160 165 170 175 horizontal curve vertical Directions down up Figure 6: Length of dragging trajectory depending on area and direction. the horizontal area (mean 1016 ms) and 10% (110 ms) longer than the dragging durations on the vertical area (mean 1056 ms). Other main effects and the interaction were not signifi- cant. Figure 6 illustrates the length of dragging trajectories. The ANOVA showed a significant main effect of the factor area (F (2, 34) = 28.84; p < 0.01). The dragging trajectories inside the curve (mean 167 px) were 3% (5 px) longer than the dragging trajectories on the horizontal area (mean 162 px). But dragging through the curve was equally long com- pared to vertical dragging (mean 168 px). Furthermore, for the horizontal plane, but not for the other areas, upward dragging was significantly shorter than downward dragging. This yielded a significant interaction (F (2, 34) = 4.73; p < 0.05). The main effect of the factor direction alone was not significant. To sum up, when comparing horizontal and vertical dragging (H1) the results clearly showed shorter trajectories for oper- ations in the horizontal plane. This is in accordance with H1. However, dragging duration was comparable for both planes. On a first glance this is not further surprising, since finger amplitude and target size remained constant over the task. So, in accordance with Fitts’ Law [9], movement durations should be constant as well. However, on a second glance the results also show that the movement plane seemed to have no ITS 2010: Displays November 7-10, 2010, Saarbrücken, Germany 6 -45˚ 45˚ -35˚ -25˚ 25˚ -15˚ 15˚ 0˚ 35˚ source positions 1 2 3 4 5 6 7 8 9 target positions Figure 7: Experimental design of cross-dragging per- formance task for upward condition. further effect on movement durations. The main finding is, that movement execution was optimized along the observed movement path. This optimization did not lead to any fur- ther improvement of movement duration, probably caused by a bottom effect—durations were very short and seemed to be already at a minimum for the given distance. Sec- ond, our results support H2: dragging on a planar surface is indeed more efficient (in terms of durations) than drag- ging across the curve. Concerning Fitts’ Law [9] this is a rather unexpected finding, as with a constant index of diffi- culty one would have expected constant movement durations over all areas. As this is clearly not the case findings sug- gest that motor control across the curve is more complex and therefore takes longer. Considering the movement path, only horizontal but not vertical dragging was superior to dragging in the curved area. This might indicate that motor control is more difficult for dragging in a curved or vertical area than in the horizontal area. Finally, we hypothesized more ef- ficient upward than downward movements (H3). Although performance data in both planar surfaces slightly hint at an advantage for upward movements, this was only significant for horizontal finger trajectories. Thus, overall the data did not confirm H3. Cross-dragging performance depending on angle With the second task we explored dragging performance not within an area (as in Task 1) but across the whole BendDesk surface and we compared if dragging performance depended on the angle of approach. Task design and procedure The experimental task is de- picted in Figure 7. Our system displayed the source, a white colored circle and the target, a black colored circle inside a white ring. Both circles had a diameter of 60 px (5.82 cm) and the thickness of the target ring amounts to 20 px (1.94 cm). The distance between source and target was 600 px (58.20 cm). As in Task 1, participants had to drag the source onto the target using the index finger. After success- fully matching source and target (within a tolerance of 10 px, px 600 610 620 630 640 650 660 670 -45◦ -35◦ -25◦ -15◦ 0◦ 15◦ 25◦ 35◦ 45◦ Figure 8: Length of dragging trajectory depending on angle. or 0.98 cm), the interactive area went blank and the next trial appeared. Trials appeared in 9 different movement directions (with two repetitions each): (1) 45◦, (2) 35◦, (3) 25◦, (4) 15◦ to the left, (5) 0◦ (vertical line), and (6) 15◦, (7) 25◦, (8) 35◦, (9) 45◦ to the right. The movement started either in the horizontal area (upward) or the vertical area (downward). The order of trials was randomized. Participants worked throughout 36 trials with their dominant hand and throughout another 36 trials with their non-dominant hand. A total of 72 dragging opera- tions were presented. Dependent variables were the same as described in Task 1. We assumed that a larger angle yields a lower dragging per- formance and higher deviation from the ideal dragging line: • H4: The dragging (a) duration and (b) trajectory increases with larger dragging angles. • H5: The deviation of trajectories increases with larger dragging angles, thus showing more variance in movement paths. Results Data were analyzed for each of the dependent vari- ables with one-factorial analyses of variances (ANOVAs) with the within-subject factors angle. For dragging durations the ANOVA revealed a significant main effect for the factor angle (F (8, 128) = 2.65; p < 0.05). Dragging durations varied between 1306 and 3806 ms. However, the differences across angles were too small to show statistical significance in post-hoc comparisons. The mean length of dragging trajectories are depicted in Fig- ure 8. We found a significant main effect of the factor angle (F (8, 128) = 8.94; p < 0.01). Post-hoc comparison showed that dragging trajectories for targets 45◦ to the left or to the right of the source (mean 652 px) were significantly longer when compared to targets vertically presented to the source (mean 631 px). Furthermore, deviation of movement trajectories from the direct connection between source and target were analyzed (Figure 9 and Figure 10). The ANOVA showed significant main effects of the factor angle for the maximum (F (8, 128) = 11.66; p < 0.01) as well as the average (F (8, 128) = 10.51; ITS 2010: Displays November 7-10, 2010, Saarbrücken, Germany 7 (a) 0◦ (b) ±15◦ (c) ±25◦ (d) ±35◦ (e) ±45◦ Figure 9: Dragging trajectories for upward dragging across the curve for different angles. Variance significantly increases with higher angles. px 10 15 20 25 30 35 -45◦ -35◦ -25◦ -15◦ 0◦ 15◦ 25◦ 35◦ 45◦ Figure 10: Average deviation from direct line between source and target depending on angle. (a) Downwards (b) Upwards Figure 11: Observed dragging trajectories that reduce exertion. p < 0.01) deviation between presented and observed ampli- tude (Figure 10). The deviation increased by 85% (12 px) for larger angles. We summarize, in accordance with H4 and H5 trajectories and the variance in movement paths increased for extreme angles. Virtual aiming at the target With the last task, we investigated virtual aiming perfor- mance across the BendDesk surface. Other than in the pre- vious tasks participants did not move their finger towards the target, but had to adjust both fingers inside the source area along a virtual aiming path to hit the target. We compared whether virtual aiming was supported with or without a grid displayed on the surface. Task design and procedure The experimental task is de- picted in Figure 12. The system displayed the source, a gray colored circle with a diameter of 200 px (19.5 cm) and the target, a white colored circle with a diameter of 30 px (2.9 cm). The distance between source and target was 800 px (78.1 cm). Participants had to position the left and right in- dex finger inside the source area until an imagined line drawn through both finger tips would hit the target area. The sys- tem gave visual feedback by rendering circles beneath the touches. When participants felt that they would have hit the target they released both fingers and the system displayed a gray line through both touches towards the target area. Then, the interactive area went blank and the next trial appeared. Trials appeared in ten different movement directions (with two repetitions each). Targets within the horizontal plane: (1) 90◦, (2) 80◦, (3) 70◦; target within the curve: (4) 60◦; and targets across the curve and in the vertical plane: (5) 50◦, (6) 40◦, (7) 30◦, (8) 20◦, (9) 10◦, and (10) 0◦. The order of trials was randomized. Participants worked throughout a block with a uniform grid on the system’s surface (we dis- played a 26 x 26 grid with a cell size of about 40 px× 40 px, or 3.9 cm × 3.9 cm) and throughout another block without a grid but a solid blue-colored surface. This resulted in 10 (angle) × 2 (background) experimental conditions. We fur- ther controlled the virtual aiming direction by presenting the source either in the right or left corner of the horizontal area (upward aiming), or in the right or left corner of the verti- cal area (downward aiming). This resulted in a total number of 160 virtual aiming operations. As dependent variable we measured the aiming error (Figure 13), i.e., the deviation be- tween the virtual aiming path and the target area, or in other words the spatial misjudgment (given in px). We hypothesized the following outcomes: • H6: The aiming error is smaller for virtual aiming within one plane than across the curve and different planes. • H7: The aiming error is smaller for virtual aiming with a grid displayed on the surface than without a grid. Results The data were analyzed with a 10 × 2 analysis of variance (ANOVA) with the within-subject factor angle and background. Aiming errors are depicted in Figure 14. The ANOVA revealed a significant main effect of the factor an- gle (F (9, 158) = 17.24; p < 0.01). Aiming errors were smallest when source and target were within the same plane, i.e., virtual aiming at 90◦ (mean error 9 px) was significantly more accurate than at all other angles (mean error 43 px).